Evolutionary Psychology and the Emotions.docx

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Evolutionary Psychology and the Emotions

Leda Cosmides & John Tooby

Evolutionary psychology is an approach to the psychological sciences in which principles and

results drawn from evolutionary biology, cognitive science, anthropology, and neuroscience are

integrated with the rest of psychology in order to map human nature. By human nature,

evolutionary psychologists mean the evolved, reliably developing, species-typical computational

and neural architecture of the human mind and brain. According to this view, the functional

components that comprise this architecture were designed by natural selection to solve adaptive

problems faced by our hunter-gatherer ancestors, and to regulate behavior so that these adaptive

problems were successfully addressed (for discussion, see Cosmides & Tooby, 1987, Tooby &

Cosmides, 1992). Evolutionary psychology is not a specific subfield of psychology, such as the

study of vision, reasoning, or social behavior. It is a way of thinkingabout psychology that can beapplied to any topic within it - including the emotions.

The analysis of adaptive problems that arose ancestrally has led evolutionary psychologists to apply

the concepts and methods of the cognitive sciences to scores of topics that are relevant to the study

of emotion, such as the cognitive processes that govern cooperation, sexual attraction, jealousy,

aggression, parental love, friendship, romantic love, the aesthetics of landscape preferences,

coalitional aggression, incest avoidance, disgust, predator avoidance, kinship, and family relations

(for reviews, see Barkow, Cosmides, & Tooby, 1992; Crawford & Krebs, 1998; Daly & Wilson,

1988; Pinker, 1997).

Indeed, a rich theory of the emotions naturally emerges out of the core principles of evolutionary

psychology (Tooby 1985; Tooby & Cosmides, 1990a; see also Nesse, 1991). In this chapter we will

(1) briefly state what we think emotions are and what adaptive problem they were designed to

solve; (2) explain the evolutionary and cognitive principles that led us to this view; and (3) using

this background, explicate in a more detailed way the design of emotion programs and the states

they create.

An evolutionary psychological theory of the emotions

An evolutionary perspective leads one to view the mind as a crowded zoo of evolved, domain-

specific programs. Each is functionally specialized for solving a different adaptive problem thatarose during hominid evolutionary history, such as face recognition, foraging, mate choice, heart

rate regulation, sleep management, or predator vigilance, and each is activated by a different set of

cues from the environment. But the existence of all these microprograms itself creates an adaptive

problem: Programs that are individually designed to solve specific adaptive problems could, if

simultaneously activated, deliver outputs that conflict with one another, interfering with or

nullifying each other's functional products. For example, sleep and flight from a predator require

mutually inconsistent actions, computations, and physiological states. It is difficult to sleep when

your heart and mind are racing with fear, and this is no accident: disastrous consequences would

ensue if proprioceptive cues were activating sleep programs at the same time that the sight of a

stalking lion was activating ones designed for predator evasion. To avoid such consequences, the

mind must be equipped with superordinate programs that override some programs when others areactivated (e.g., a program that deactivates sleep programs when predator evasion subroutines are

activated). Furthermore, many adaptive problems are best solved by the simultaneous activation of


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many different componentsof the cognitive architecture, such that each component assumes one of

several alternative states (e.g., predator avoidance may require simultaneous shifts in both heart rate

and auditory acuity; see below). Again, a superordinate program is needed that coordinates these

components, snapping each into the right configuration at the right time.

Emotions are such programs. To behave functionally according to evolutionary standards, the

mind's many subprograms need to be orchestrated so that their joint product at any given time isfunctionally coordinated, rather than cacophonous and self-defeating. This coordination is

accomplished by a set of superordinate programs - the emotions. They are adaptations that have

arisen in response to the adaptive problem of mechanism orchestration (Tooby & Cosmides, 1990a;

Tooby, 1985). In this view, the exploration of the statistical structure of ancestral situations and

their relationship to the mind's battery of functionally specialized programs is central to mapping

the emotions. This is because the most useful (or least harmful) deployment of programs at any

given time will depend critically on the exact nature of the confronting situation.

How did emotions arise and assume their distinctive structures? Fighting, falling in love, escaping

predators, confronting sexual infidelity, experiencing a failure-driven loss in status, responding to

the death of a family member (and so on) each involved conditions, contingencies, situations, orevent-types that recurred innumerable times in hominid evolutionary history. Repeated encounters

with each kind of situation selected for adaptations that guided information-processing, behavior

and the body adaptively through the clusters of conditions, demands, and contingencies that

characterized that particular class of situation. This could be accomplished by engineering

superordinate programs, each of which jointly mobilizes a subset of the psychological architecture's

other programs in a particular configuration. Each configuration would be selected to deploy

computational and physiological mechanisms in a way that, when averaged over individuals and

generations, would have led to the most fitness-promoting subsequent lifetime outcome given that

ancestral situation-type.

This coordinated adjustment and entrainment of mechanisms is a mode of operation for the entire

psychological architecture, and serves as the basis for a precise computational and functional

definition of each emotion state (Tooby & Cosmides, 1990a; Tooby, 1985). Each emotion entrains

various other adaptive programs - deactivating some, activating others, and adjusting the modifiable

parameters of still others - so that the whole system operates in a particularly harmonious and

efficacious way when the individual is confronting certain kinds of triggering conditions or

situations. The conditions or situations relevant to the emotions are those that (1) recurred

ancestrally; (2) could not be negotiated successfully unless there was a superordinate level of

program coordination (i.e., circumstances in which the independent operation of programs caused

no conflicts would not have selected for an emotion program, and would lead to emotionally neutral

states of mind); (3) had a rich and reliable repeated structure; (4) had recognizable cues signalingtheir presence; and (5) in which an error would have resulted in large fitness costs (Tooby &

Cosmides, 1990a; Tooby, 1985). When a condition or situation of an evolutionarily recognizable

kind is detected, a signal is sent out from the emotion program that activates the specific

constellation of subprograms appropriate to solving the type of adaptive problems that were

regularly embedded in that situation, and deactivates programs whose operation might interfere

with solving those types of adaptive problem. Programs directed to remain active may be cued to

enter subroutines that are specific to that emotion mode, and that were tailored by natural selection

to solve the problems inherent in the triggering situation with special efficiency.

According to this theoretical framework, an emotion is a superordinate program whose function is

to direct the activities and interactions of the subprograms governing perception; attention;inference; learning; memory; goal choice; motivational priorities; categorization and conceptual

frameworks; physiological reactions (such as heart rate, endocrine function, immune function,


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gamete release); reflexes; behavioral decision rules; motor systems; communication processes;

energy level and effort allocation; affective coloration of events and stimuli; recalibration of

probability estimates, situation assessments, values, and regulatory variables (e.g., self-esteem,

estimations of relative formidability, relative value of alternative goal states, efficacy discount rate);

and so on. An emotion is not reducible to any one category of effects, such as effects on physiology,

behavioral inclinations, cognitive appraisals, or feeling states, because it involves evolved

instructions for all of them together, as well as other mechanisms distributed throughout the humanmental and physical architecture.

All cognitive programs - including superordinate programs of this kind - are sometimes mistaken

for "homunculi", that is, entities endowed with "free will". A homunculus scans the environment

and freely chooses successful actions in a way that is not systematic enough to be implemented by a

program. It is the task of cognitive psychologists to replace theories that implicitly posit such an

impossible entity with theories that can be implemented as fixed programs with open parameters.

Emotion programs, for example, have a front end that is designed to detect evolutionarily reliable

cues that a situation exists (whether or not these cues reliably signal the presence of that situation in

the modern world); when triggered, they entrain a specific set of subprograms: those that natural

selection "chose" as most useful for solving the problems that situation posed in ancestralenvironments. Just as a computer can have a hierarchy of programs, some of which control the

activation of others, the human mind can as well. Far from being internal free agents, these

programs have an unchanging structure regardless of the needs of the individual or her

circumstances, because they were designed to create states that worked well in ancestral situations,

regardless of their consequences in the present.

Fear (an example)

Consider the following example. The ancestrally recurrent situation is being alone at night and a

situation-detector circuit perceives cues that indicate the possible presence of a human or animal

predator. The emotion mode is a fear of being stalked. (In this conceptualization of emotion, there

might be several distinct emotion modes that are lumped together under the folk category "fear", but

that are computationally and empirically distinguishable by the different constellation of programs

each entrains.) When the situation detector signals that one has entered the situation "possible

stalking and ambush", the following kinds of mental programs are entrained or modified: (1) There

are shifts in perception and attention: You may suddenly hear with far greater clarity sounds that

bear on the hypothesis that you are being stalked, but that ordinarily you would not perceive or

attend to, such as creaks or rustling. Are the creaks footsteps? Is the rustling caused by something

moving stealthily through the bushes? Signal detection thresholds shift: Less evidence is required

before you respond as if there were a threat, and more true positives will be perceived at the cost of

a higher rate of false alarms. (2) Goals and motivational weightings change: Safety becomes a farhigher priority. Other goals and the computational systems that subserve them are deactivated: You

are no longer hungry; you cease to think about how to charm a potential mate; practicing a new skill

no longer seems rewarding. Your planning focus narrows to the present: worries about yesterday

and tomorrow temporarily vanish. Hunger, thirst, and pain are suppressed. (3) Information-

gathering programs are redirected: Where is my baby? Where are others who can protect me? Is

there somewhere I can go where I can see and hear what is going on better? (4) Conceptual frames

shift, with the automatic imposition of categories such as "dangerous" or "safe". Walking a familiar

and usually comfortable route may now be mentally tagged as "dangerous". Odd places that you

normally would not occupy - a hallway closet, the branches of a tree - suddenly may become salient

as instances of the category "safe" or "hiding place". (5) Memory processes are directed to new

retrieval tasks: Where was that tree I climbed before? Did my adversary and his friend look at mefurtively the last time I saw them? (6) Communication processes change: Depending on the

circumstances, decision rules might cause you to emit an alarm cry, or be paralyzed and unable to


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speak. Your face may automatically assume a species-typical fear expression. (7) Specialized

inference systems are activated: Information about a lion's trajectory or eye direction might be fed

into systems for inferring whether the lion saw you. If the inference is yes, then a program

automatically infers that the lion knows where you are; if no, then the lion does not know where

you are (the "seeing-is-knowing" circuit identified by Baron-Cohen 1995, and inactive in autistics).

This variable may automatically govern whether you freeze in terror or bolt. Are there cues in the

lion's behavior that indicate whether it has eaten recently, and so is unlikely to be predatory in thenear future? (Savanna ungulates, such as zebras and wildebeests, commonly make this kind of

judgment; Marks, 1987). (8) Specialized learning systems are activated, as the large literature on

fear conditioning indicates (e.g., LeDoux, 1995; Mineka & Cook, 1993; Pitman & Orr, 1995). If the

threat is real, and the ambush occurs, the victim may experience an amygdala-mediated

recalibration (as in post-traumatic stress disorder) that can last for the remainder of his or her life

(Pitman & Orr, 1995). (9) Physiology changes: Gastric mucosa turn white as blood leaves the

digestive tract (another concomitant of motivational priorities changing from feeding to safety);

adrenalin spikes; heart rate may go up or down (depending on whether the situation calls for flight

or immobility), blood rushes to the periphery, and so on (Cannon, 1929; Tomaka, Blascovich,

Kibler, & Ernst, 1997); instructions to the musculature (face, and elsewhere) are sent (Ekman,

1982). Indeed, the nature of the physiological response can depend in detailed ways on the nature ofthe threat and the best response option (Marks, 1987). (10) Behavioral decision rules are activated:

Depending on the nature of the potential threat, different courses of action will be potentiated:

hiding, flight, self-defense, or even tonic immobility (the latter is a common response to actual

attacks, both in other animals and in humans). Some of these responses may be experienced as

automatic or involuntary.

From the point of view of avoiding danger, these computational changes are crucial: They are what

allowed the adaptive problem to be solved with high probability, on average over evolutionary time.

Of course, in any single case they may fail, because they are only the evolutionarily-computed best

bet, based on ancestrally summed outcomes; they are not a sure bet, based on an unattainable

perfect knowledge of the present. Whether individuals report consciously experiencing fear is aseparate question from whether their mechanisms assumed the characteristic configuration that,

according to this theoretical approach, defines the fear emotion state. Individuals often behave as if

they are in the grip of an emotion, while denying they are feeling that emotion. We think it is

perfectly possible that individuals sometimes remain unaware of their emotion states, which is one

reason we do not use subjective experience as thesine qua nonof emotion. At present, both the

function of conscious awareness, and the principles that regulate conscious access to emotion states

and other mental programs are complex and unresolved questions. Mapping the design features of

emotion programs can proceed independently of their resolution, at least for the present.

With the preceding view of emotions in mind, in the next section we will outline the evolutionaryand cognitive principles that led us to it (detailed arguments for these positions can be found in

Tooby & Cosmides, 1992, 1990a, and 1990b, and in Cosmides & Tooby 1987, 1992, 1997).

Evolutionary foundations

Chance and selection.For reasons researchers have only recently come to fully appreciate, every

species has a universal, species-typical evolved architecture (Tooby & Cosmides, 1990b). These

designs are largely conserved through genetic inheritance from generation to generation (accounting

over the long term for homologous similarities among related species). Nevertheless, over the long

run, evolutionary change takes place, and this design modification is governed by two kinds of

processes: chance and selection. Random mutations are always being injected into species. Whatultimately happens to each mutation is shaped both by chance and by the stable consequences the

mutation has on the design of the organism -- selection. A mutational modification to a design


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feature will often alter how well it functions (e.g. improving the optics of the lens, or reducing a

liver enzyme's detoxification efficiency). Those alterations that improve the machine's ability to

solve reproduction-promoting tasks (compared to the earlier model design feature) will increase

their own frequency over the generations, until (usually) they become universally incorporated into

the species design. The accumulated effects of this positive feedback is one reason why species tend

to have universal, species-typical evolved architecture in their functional components (see Tooby &

Cosmides, 1990b for details and exceptions). Other modifications interfere with replication: theseact to edit themselves from the population and the species design (negative feedback). Still others

have no systematic effect: neutral alterations randomly drift in frequency, sometimes disappearing

and sometimes becoming species-typical. These processes - chance and selection - explain how

species acquired their designs.

For researchers seeking to understand organic design, natural selection is the most important

component to consider, because it is the only force in nature that can build functional organization

into organisms. Natural selection is a hill-climbing feedback process that chooses among alternative

designs on the basis of how well they function . This is what biologists mean when they say that

function determines structure. Natural selection is a causal process in which a structure

spreads because of its functional consequences. This causal relationship is what gives theories ofadaptive function their heuristic power for psychologists and biologists. If one knows what adaptive

problems our ancestors faced generation after generation, one can look for mechanisms that are

well-engineered for solving them.

Because of the different roles played by chance and selection, the evolutionary process builds three

different types of outcomes into organisms: (1) adaptations, that is, functional machinery built by

selection (usually species-typical), (2) byproducts of adaptations, which are present in the design of

organisms because they are causally coupled to traits that were selected for (usually species-

typical), and (3) random noise, injected by mutation and other random processes (often not species-

typical) (Tooby & Cosmides, 1990a, 1990b, 1992; Williams, 1966). The emotion of sexual jealousy

is an adaptation (Daly, Wilson & Weghorst, 1982; Buss, 1994); stress-induced physical

deterioration is arguably a byproduct of the flight-fight system; and heritable personality variation

in emotional functioning (e.g., extreme shyness, morbid jealousy, bipolar depression) is probably

noise (Tooby & Cosmides, 1990b). Evidence of the presence (or absence) of high degrees of

coordination between adaptive problems and the design features of putative adaptations allows

researchers to distinguish adaptations, byproducts, and noise from one another (Williams, 1966;

Cosmides & Tooby, 1997).

How well -designed are emotion adaptations expected to be? Organisms, as a result of millions of

years of selection, are full of evolved adaptations that are improbably well-engineered to solve the

adaptive problems the species encountered repeatedly during its evolution. Biologists have foundthat selection has routinely produced exquisitely engineered biological machines of the highest

order, at all scales, from genetic error correction and quality control in protein assembly to

photosynthetic pigments, the immune system, the vertebrate eye and visual system, efficient bee

foraging algorithms, echolocation, and color constancy systems. While Stephen Jay Gould (1997)

and his followers have energetically argued in the popular science literature that natural selection is

a weak evolutionary force, evolutionary biologists, familiar with the primary literature, have found

it difficult to take these arguments seriously (Tooby & Cosmides, under review).

In fact, whenever the adaptive problem can be well-specified (as in color constancy, object

recognition, grammar acquisition, word meaning induction, tactile perception, chemical

identification), natural computational adaptations have consistently and strikingly outperformed thebest artificial devices that teams of engineers, using decades of effort, and millions of dollars of

funding, have produced (consider, e.g., artificial vision or speech recognition programs). So while


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adaptations are in some abstract sense undoubtedly far from optimal, they are nevertheless

extremely well-engineered, and their performance on the problems they evolved to solve is

unrivaled by any machine yet designed by humans. The empirical evidence falsifies the claim that

evolved computational adaptations tend to be crude or primitive in design, and supports the

opposite view: that our mental machinery, including the emotions, are likely to be very well-

designed to carry out evolved functions. For emotion researchers, this means that one's working

hypotheses (which are always open to empirical revision) should begin with the expectation of highlevels of evolutionary functionality, and one's research methods should be sensitive enough to

detect such organization. This does not mean that emotions are well-designed for the modern world

-- only that their functional logic is likely to be sophisticated and well-engineered to solve ancestral

adaptive problems.

Adaptive problems. Over evolutionary time, design features are added to or discarded from the

species' design because of their consequences. A design feature will cause its own spread over

generations if it has the consequence of solving adaptive problems such as detecting predators,

deterring sexual rivals, helping sisters, or ejecting toxin-laden food.Adaptive problemsare

evolutionarily long-enduring recurring clusters of conditions that constitute either reproductive

opportunities (e.g., the arrival of a potential mate; the reflectant properties of light) or reproductiveobstacles (e.g., the speed of a prey animal; the actions of a sexual rival, limited food supplies for

relatives). Adaptations were designed by selection to exploit these opportunities and to circumvent

these obstacles. A design feature may be said to solve an adaptive problem to the extent that its

presence in an organism (when compared to alternative designs) increases the organism's net

lifespan reproduction, and the reproduction of kin (who are likely to carry the same genetically

based design feature; Hamilton, 1964).

Researchers less familiar with evolutionary psychology often equate adaptive problems exclusively

with short-run threats to physical survival. However, survival is not central to evolution: indeed, all

individual organisms die sooner or later. In contrast, genes - which can be thought of as particles of

design - are potentially immortal, and design features spread by promoting the reproduction of the

genes that participate in building them. Survival is significant only insofar as it promotes the

reproduction of design features. It is no more significant than anything else that promotes

reproduction, and is often advantageously risked or sacrificed in the process of promoting

reproduction in self, children, or other relatives.

Because events and conditions in the organism's local world are causally linked, the enhancement of

its reproduction reaches out to encompass, in a network of causal linkages, all of human life, from

the subtleties of facial expression to attributions of responsibility to the intrinsic rewards of

projectile games to the ability to imagine alternatives. The realm of adaptive information-processing

problems is not limited to one area of human life, such as sex, violence, or resource acquisition.Instead, it is a dimension cross-cutting all areas of human life, as weighted by the strange,

nonintuitive metric of their cross-generational statistical effects on direct and kin reproduction.

Moreover, it is important to remember that the consequences at issue in a good design are total

lifetime fitness consequences, not just what happens in the short run. The design features of every

program have been shaped by the answer to the question: Given the situation the organism is in at

each given present moment, what is the deployment at that moment of the modifiable characteristics

of the individual (physiology, action, knowledge states, etc.) that will net the best return on own and

kin reproduction, as accrued over the expected remainder of the individual's lifespan? Emotion

programs that incline the individual to engage in seemingly pointless activities over the near-term

(e.g., grief, playfulness, fascination, guilt, depression, feeling triumphant) need to be analyzed interms of how they modify the psychological architecture for benefits that are accrued

probabilistically over the long-run (e.g., gains in knowledge; recalibration of motivational priorities;


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the recomputation of a huge body of choice-variables in the face of information that the local world

has dramatically changed).

The envi ronment of evolu tionary adaptedness. Behavior in the present is generated by evolved

information-processing mechanisms that were constructed in the past because they solved adaptive

problems in the ancestral environments in which the human line evolved. For this reason,

evolutionary psychology is both environment-oriented and past-oriented in its functionalistorientation. Adaptations become increasingly effective as selection makes their design features

more and more complementary to the long-enduring structure of the world. The articulated features

of the adaptation are designed to mesh with the features of the environment that were stable during

the adaptation's evolution, so that their interaction produced functional outcomes. The regulation of

breathing assumes the presence of certain long-enduring properties of the atmosphere and the

respiratory system. Vision assumes the presence of certain evolutionarily stable properties of

surfaces, objects, and terrestrial spectral distributions. The lactase digestive enzyme presupposes an

infant diet of milk with lactose. And each emotion presupposes that certain cues signal the presence

of a structure of events and conditions that held true during the evolution of that emotion. Disgust

circuits presume a world in which rotten smells signal toxins or microbial contamination, for

example.

Accordingly, to understand an adaptation as a problem-solver, one needs to model the enduring

properties of the task-environment that selected for that adaptation -- the environment of

evolutionary adaptedness, or EEA. Although the hominid line is thought to have first differentiated

from the chimpanzee lineage on the African savannas and woodlands, the EEA is not a place or

time. It is the statistical composite of selection pressures that caused the genes underlying the design

of an adaptation to increase in frequency until they became species-typical or stably persistent

(Tooby & Cosmides, 1990a). Thus, statistical regularities define the EEA for any given adaptation.

The conditions that characterize the EEA are usefully decomposed into a constellation of specific

environmental regularities that had a systematic (though not necessarily unvarying) impact on

reproduction and that endured long enough to work evolutionary change on the design of an

adaptation. These regularities can include complex conditionals (e.g., if one is male hunter-

gatherer andone is having a sexual liaison with someone else's mate and that is discovered, then

one is the target of lethal retributory violence 37% of the time). Descriptions of these statistical

regularities are essential parts of the construction of a task analysis of the adaptive problem a

hypothesized adaptation evolved to solve (Tooby & Cosmides, 1990a). Conceptualizing the EEA in

statistical terms is fundamental to the functional definition of emotion that we presented above and

will elucidate below.

Cognitive foundations

The cognit ive science resolu tion of the mind-body problem. Evolutionary psychology starts with a

fundamental insight from cognitive psychology: The brain is a machine designed to process

information. From this perspective, one can define the mind as a set of information-processing

procedures (cognitive programs) that are physically embodied in the neural circuitry of the brain.

For cognitive scientists, brainand mindare terms that refer to the same system, which can be

described in two complementary ways - either in terms of its physical properties (the neural), or in

terms of its information-processing operation (the mental). The mind is what the brain does,

described in computational terms (Jackendoff, 1987; Cosmides & Tooby, 1987; Pinker, 1997). This

approach allows mental operations to be described with great precision: one is led to specify what

information is extracted from the environment, what procedures act to transform it, what formats

are involved in its representation or storage, and what operations access it to govern decision-making, physiological or behavioral regulation, or further information integration. Also, because it

provides an intelligible way of relating physical and mental phenomena, discoveries in brain science


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(e.g., from dissociation studies and neuroimaging) can be used in making inferences about the mind,

and vice versa - a process that is leading to a principled mapping between brain and mind (for

reviews, see, Gazzaniga, 1995, 2000).

An evolutionary perspective makes clear why the cognitive or computational level of description is

more than an analogy. Whereas other parts of the body were designed for lifting loads, grinding

food, chemically extracting nutrients, and so on, the brain was designed by evolution to useinformation derived from the environment and the body to functionally regulate behavior and the

body. The brain came into existence and, over evolutionary time, accreted its present complex

structure because, in ancestral populations, mutations that created or altered cognitive programs

such that they more successfully carried out adaptively consequential information-processing tasks

were differentially retained, replicated, and incorporated into our species' neural design.

The ancestral world posed recurrent information-processing problems, such as What substances are

best to eat? or What is the relationship between others' facial expressions and their mental states?

Information-processing programs - food preferences and aversions, or rules for inferring emotions

from facial expressions - acquired one set of design features rather than many others because the

retained features better computed solutions to these information-processing problems. Overevolutionary time, it was the computationalproperties of alternative neural circuits - their relative

ability to solve adaptive information-processing tasks - that caused some neural circuits to be

selected for, and others to be selected out. So, from an evolutionary and a functional point of view,

the brain is intrinsically and by its nature an organ of computation - a set of information-processing

devices realized in neural tissue (Cosmides & Tooby, 1987; Tooby & Cosmides, 1992; Pinker,

1997). A key task for psychologists, then, is to discover, inventory and map the "circuit logic" of

the collection of programs that constitute the human mind, and relate how that adaptive logic maps

onto the suite of informational problems faced by our hunter-gatherer ancestors.

Emotion and computation.It may strike some as odd to speak about love or jealousy or disgust in

computational terms. "Cognition" and "computation" have affectless, flavorless connotations. In

everyday language, the term "cognition" is often used to refer to a particular subsetof information-

processing - roughly, the effortful, conscious, voluntary, deliberative kind of thinking one does

when solving a mathematics problem or playing chess: what is sometimes called "cold cognition".

This use of "cognition" falls out of the folk psychological classification of thinking as distinct from

feeling and emotion, and it appears in a few subfields of psychology as well (particularly those

concerned with education and the acquisition of skills that must be explicitly taught). As a result,

one sometimes sees articles in the psychological literature on how emotion, affect, or mood

influence "cognition".

However, from an evolutionary cognitive perspective, one cannot sensibly talk about emotionaffecting cognition because cognition refers to a language for describing all of the brain's

operations, including emotions and reasoning (whether deliberative or nonconscious), and not to

any particular subset of operations. If the brain evolved as a system of information-processing

relations, then emotions are, in an evolutionary sense, best understood as information-processing

relations - i.e., programs - with naturally selected functions. Initially, the commitment to exploring

the underlying computational architecture of the emotions may strike one as odd or infelicitous, but

it leads to a large number of scientific payoffs, as we will sketch out below.

Thus, the claim that emotion is computational does not mean that an evolutionary psychological

approach reduces the human experience to bloodless, affectless, disembodied ratiocination. Every

mechanism in the brain - whether it does something categorizable as "cold cognition" (such asinducing a rule of grammar or judging a probability) or as "hot cognition" (such as computing the

intensity of parental fear, the imperative to strike an adversary, or an escalation in infatuation) -


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depends on an underlying computational organization to give its operation its patterned structure, as

well as a set of neural circuits to physically implement it.

Of course, shifting terminology (e.g., from "cognition" as thinking to "cognition" as everything

mental) does nothing to invalidate research done with the old terminology, and valuable research

has been done exploring how various emotion states modify performance on tasks that require

deliberative thinking (e.g., Isen, 1987; Mackie & Worth, 1991). But an evolutionary andcomputational view of emotion can open up for exploration new empirical possibilities obscured by

other frameworks. An evolutionary perspective breaks categories like "thinking" into a large set of

independent domain-specific programs, and so opens up the possibility that distinct emotions affect

separate inference programs in diverse, yet functionally patterned, ways, rather than in a single,

aggregate way.

Domain specif ici ty and functional speciali zation. A basic engineering principle is that the same

machine is rarely capable of solving two different problems equally well. Cork-screws and cups

have different properties because they are solutions to different problems, and each therefore solves

its targeted problem better than the other. Similarly, natural selection has constructed different

tissues and organs, like the heart for pumping blood and the liver for detoxifying poisons, forexactly this reason. This same principle applies to our evolved cognitive programs and neural

circuitry. Different information-processing problems usually require different procedures for their

successful solution. For example, to solve the adaptive problem of selecting a good mate, one's

choices must be guided by qualitatively different standards than when choosing the right food, or

the right habitat, or the right meaning for an unfamiliar word. Implementing different solutions

requires different, functionally distinct mechanisms (Sherry & Schacter, 1987; Gallistel, 1995).

Speed, reliability, and efficiency can be engineered into specialized mechanisms because they do

not need to make trade-offs between mutually incompatible task demands, and because they can use

problem-solving principles that work in one domain but not in others. (For detailed arguments, both

on the weakness of domain-general architectures and on the many advantages of architectures that

include a large number of domain-specific computational devices, see Cosmides & Tooby, 1987,

1994; Tooby & Cosmides, 1990a, 1992).

The application of these principles to the design of the mind has convinced many scientists,

including most evolutionary psychologists, that the human cognitive architecture is multimodular:

that it is composed of a large number of information-processing programs, many of which are

functionally specialized for solving a different adaptive problem. These adaptations appear to be

domain-specific expert systems, equipped with "crib sheets": inference procedures, regulatory rules,

motivational priorities, goal-definitions, and assumptions that embody knowledge, regulatory

structure, and value weightings specific to an evolved problem domain. These generate correct (or,

at least, adaptive) outputs that would not be warranted on the basis of perceptual data processedthrough some general-purpose decisional algorithm. In the last two decades, many cognitive

researchers have found evidence for the existence a diverse collection of inference systems,

including specializations for reasoning about objects, physical causality, number, language, the

biological world, the beliefs and motivations of other individuals, and social interactions (for

reviews, see Hirschfeld & Gelman, 1994; Cognitive Science, volume 14 (1990), and Barkow,

Cosmides and Tooby, 1992). These domain-specific inference systems have a distinct advantage

over domain-independent ones, akin to the difference between experts and novices: experts can

solve problems faster and more efficiently than novices because they already know a lot about the

problem domain, and because they are equipped with specialized tools and practices.

Each adaptive problem recurred millions of times in the EEA, and so manifested a statistical andcausal structure whose elements were available for specialized exploitation by design features of the

evolving adaptation. For example, predators use darkness and cover to ambush. Physical


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appearance varies with fertility and health. Children one's mother regularly feeds are usually genetic

siblings. Specialized programs - for predator fear, sexual attraction, and incest avoidance,

respectively - could evolve whose configuration of design features embodied and/or exploited these

statistical regularities, allowing these adaptive problems to be solved economically, reliably, and

effectively. Such specializations, by embodying "innate knowledge" about the problem space,

operate better than any general learning strategy could. A child did not have to wait to be ambushed

and killed in the dark to prudently modulate her activities. Adults did not need to observe thenegative effects of incest, because the Westermarck mechanism mobilizes disgust towards having

sex with likely siblings (Shepher 1983).

Selection detects the individuall y unobservable. Animals subsist on information. The single most

limiting resource to reproduction is not food or safety or access to mates, but what makes them each

possible: the information required for making adaptive behavioral choices. However, many

important features of the world cannot be perceived directly. Cognitive adaptations can use

perceivable events as cues for inferring the status of important, nonperceivablesets of conditions,

provided there was a predictable probabilistic relationship between them that was maintained over

evolutionary time. Natural selection can extract statistical relationships that would be undetectable

to any individual organism (Cosmides & Tooby, 1987; Tooby & Cosmides, 1990a). It does this bytesting randomly generated alternative designs, each of which embodies different assumptions about

the structure of the world, and retaining the ones that succeed most effectively. The most effective

design will be the one that best embodies design features that reflect most closely the actual long-

term statistical structure of the ancestral world. Designs whose features exploited these real but

ontogenetically unobservable relationships outperformed those that depended on different

relationships, or that only responded to conditions the individual could observe during her lifetime.

This is why tabula rasa models of human and nonhuman minds are evolutionarily impossibilities

(Cosmides & Tooby, 1987). For example, the negative effects of incestuous conceptions are

difficult for any individual to observe in the absence of a modern controlled study with numerous

participants, much less integrate rationally into one's motivational system. Fortunately, the

consequences of incest over evolutionary time selected for specialized disgust mechanisms that

reflected the ancestral distribution of choice-consequence pairings, and so are designed to guide

humans away from incestuous unions between fertile adults, given appropriate cues of familial

connection such as co-residence in the first years of life (Shepher, 1983). Evolved psychological

adaptations are selected to use cues that (1) can be reliably and easily detected by the individual,

and (2) reliably predicted the hidden structure of conditions relevant to determining which course of

action one should take.

The functional structure of an emotion program evolved to match the evolutionari ly summed

structure of i ts target situation. The set of human emotion programs assumed their evolved designsthrough interacting with the statistically defined structure of human environments of evolutionary

adaptedness. Each emotion program was constructed by a selective regime imposed by a particular

evolutionarily recurrent situation. By an evolutionarily recurrent situation, we mean a cluster of

repeated probabilistic relationships among events, conditions, actions, and choice-consequences,

that endured over a sufficient stretch of evolutionary time to have had selective consequences on the

design of the mind, and that were probabilistically associated with cues detectable by humans.

For example, the condition of having a mate plus the condition of one's mate copulating with

someone else constitutes a situation of sexual infidelity: a situation that has recurred over

evolutionary time, even though it has not happened to every individual. Associated with this

situation were cues reliable enough to allow the evolution of a "situation detector" (e.g., observing asexual act, flirtation, or even the repeated simultaneous absence of the suspected lovers are cues that

could trigger the categorization of a situation as one of infidelity). Even more importantly, there


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were many necessarily or probabilistically associated elements that tended to be present in the

situation of infidelity as encountered among our hunter-gatherer ancestors. Additional elements

include: (1) a sexual rival with a capacity for social action and violence, as well as allies of the

rival; (2) a discrete probability that one's mate has conceived with the sexual rival; 3) changes in the

net lifetime reproductive returns of investing further in the mating relationship; (4) a probable

decrease in the degree to which the unfaithful mate's mechanisms value the victim of infidelity (the

presence of an alternative mate lowers replacement costs); (5) a cue that the victim of the infidelitywill likely have been deceived about a range of past events, leading the victim to confront the

likelihood that his or her memory is permeated with false information; (6) the victim's status and

reputation for being effective at defending his or her interests in general would be likely to

plummet, inviting challenges in other arenas. These are just a few of the many factors that constitute

a list of elements associated in a probabilistic cluster, and that constitute the evolutionary recurrent

structure of a situation of sexual infidelity. The emotion of sexual jealousy evolved in response to

these properties of the world, and there should be evidence of this in its computational design.

Emotion programs have evolved to take such elements into account, whether they can be perceived

or not. Thus, not only do cues of a situation trigger an emotion mode, but embedded in that emotion

mode is a way of seeing the world and feeling about the world related to the ancestral cluster ofassociated elements. Depending on the intensity of the jealousy evoked, less and less evidence will

be required for an individual to believe that these conditions apply to their personal situation.

Individuals with morbid jealousy, for example, may hallucinate counterfactual but evolutionarily

thematic contents.

To the extent that situations exhibit a structure repeated over evolutionary time, their statistical

properties will be used as the basis for natural selection to build an emotion program whose detailed

design features are tailored for that situation. This is accomplished by selection, acting over

evolutionary time, differentially incorporating program components that dovetail with individual

items on the list of properties probabilistically associated with the situation.

For example, if in ancestral situations of sexual infidelity there was a substantially higher

probability of a violent encounter than in its absence, then the sexual jealousy program will have

been shaped by the distillation of those encounters, and the jealousy subroutines will have been

adjusted to prepare for violence in proportion to the raised probability in the ancestral world.

(Natural selection acts too slowly to have updated the mind to post-hunter-gatherer conditions.)

Each of these sub-elements and the adaptive circuits they require can be added together to form a

general theory of sexual jealousy.

The emotion of sexual jealousy constitutes an organized mode of operation specifically designed to

deploy the programs governing each psychological mechanism so that each is poised to deal withthe exposed infidelity: physiological processes are prepared for such things as violence, sperm

competition, and the withdrawal of investment; the goal of deterring, injuring, or murdering the

rival emerges; the goal of punishing, deterring, or deserting the mate appears; the desire to make

oneself more competitively attractive to alternative mates emerges; memory is activated to

reanalyze the past; confident assessments of the past are transformed into doubts; the general

estimate of the reliability and trustworthiness of the opposite sex (or indeed everyone) may decline;

associated shame programs may be triggered to search for situations in which the individual can

publicly demonstrate acts of violence or punishment that work to counteract an (imagined or real)

social perception of weakness; and so on.

It is the relationship between the summed details of the ancestral condition and the detailedstructure of the resulting emotion program that makes this approach so useful for emotion

researchers. Each functionally distinct emotion state - fear of predators, guilt, sexual jealousy, rage,


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grief, and so on - will correspond to an integrated mode of operation that functions as a solution

designed to take advantage of the particular structure of the recurrent situation or triggering

condition to which that emotion corresponds. This approach can be used to create theories of each

individual emotion, through three steps: (1) Reconstructing the clusters of properties of ancestral

situations; (2) Constructing engineering analyses about how each of the known or suspected

psychological mechanisms in the human mental architecture should be designed to deal with each

ancestral condition or cluster of conditions, and integrating these into a model of the emotionprogram; (3) Constructing or conducting experiments and other investigations to test, and revise the

models of emotion programs.

It is also important to understand that evolutionarily recurrent situations can be arrayed along a

spectrum in terms of how rich or skeletal is the set of probabilistically associated elements that

defines the situation. A richly structured situation, such as sexual infidelity or predator ambush will

support a richly substructured emotion program in response to the many ancestrally correlated

features: Many detailed adjustments will be made to many psychological mechanisms as

instructions for the mode of operation. In contrast, some recurrent situations have less structure (i.e.,

they share fewer properties in common), and so the emotion mode makes fewer highly specialized

adjustments, imposes fewer specialized and compelling interpretations and behavioral inclinations,and so on. For example, surges of happiness or joy are an emotion program that evolved to respond

to the recurrent situation of encountering unexpected positive events (as will be explained). The

class of events captured by "unexpectedly positive" is extremely broad, general, and have only a

few additional properties in common. Emotion programs at the most general and skeletal end of this

spectrum correspond to what some call "mood" (happiness, sadness, excitement, anxiety,

playfulness, homesickness, and so on).

How to characterize an emotion

To characterize an emotion adaptation, one must identify the following properties of environments

and of mechanisms.

1)An evolutionarily recurrent situation or condition: A repeated structure of environmental and

organismic properties, characterized as a complex statistical composite of how such properties

covaried in the environment of evolutionary adaptedness. Examples of situations are being in a

depleted nutritional state, competing for maternal attention, being chased by a predator, being about

to ambush an enemy, having few friends, experiencing the death of a spouse, being sick, having

experienced a public success, having others act in a way that damages you without regard for your

welfare, having injured a valued other through insufficient consideration or self-other behavioral

trade-offs; having a baby.

2) The adaptive problem: The identification of which organismic states and behavioral sequences

will lead to the best average functional outcome for the remainder of the lifespan, given the

situation or condition. For example, what is the best course of action when others take the products

of your labor without your consent? What is the best course of action when you are in a depleted

nutritional state? What is the best course of action when a sibling makes a sexual approach?

3) Cues that signal the presence of the situation: For example, low blood sugar signals a depleted

nutritional state, the looming approach of a large fanged animal signals the presence of a predator,

seeing your mate having sex with another signals sexual infidelity; finding yourself often alone,

rarely the recipient of beneficent acts, or actively avoided by others signals that you have few

friends.


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4) Situation-detecting algorithms. A multimodular mind must be full of "demons": algorithms that

detect situations. The New Hacker's Dictionarydefines a "demon" as a "portion of a program that is

not invoked explicitly, but that lies dormant waiting for some condition(s) to occur." (Raymond,

1991, p. 124). Situation-detecting subprograms lie dormant, until they are activated by a specific

constellation of cues that precipitates the analysis of whether a particular ancestral situation has

arisen. If the assessment is positive, it sends the signal that activates the associated emotion

program. Emotion demons need two kinds of subroutines:

(a)Algorithms that monitor for situation-defining cues: These include perceptual mechanisms,

proprioceptive mechanisms, and situation-modeling memory. They take the cues in (3) as input.

(b)Algorithms that detect situations: these programs take the output of the monitoring algorithms

and targeted memory registers in (a) as input, and through integration, probabilistic weighting, and

other decision criteria, identify situations as absent or present with some probability.

The assignment of a situation interpretation to present circumstances involves a problem in signal

detection theory (Swets, Tanner & Birdsall 1964; see also Gigerenzer & Murray 1987). Animals

should be designed to "detect" what situation they are in on the basis of cues, stored variables, andspecialized interpretation algorithms. Selection will not shape decision rules so that they act solely

on the basis of what is most likely to be true, but rather on the basis of the weighted consequences

of acts given that something is held to be true. Should you walk under a tree that might conceal a

predator? Even if the algorithms assign a 51% (or even 98%) probability to the tree being predator-

free, under most circumstances an evolutionarily well-engineered decision rule should cause you to

avoid the tree - to act as if the predator were in it. The benefits of calories saved via a shortcut,

scaled by the probability that there is no predator in the tree, must be weighed against the benefits

of avoiding becoming catfood, scaled by the probability that there is a predator in the tree. Because

the costs and benefits of false alarms, misses, hits, and correct rejections are often unequal, the

decision rules may still treat as true situations that are unlikely to be true. In the modern world, this

behavior may look "irrational" (as is the case with many phobias), but we do it because such

decisions were adaptive under ancestral conditions.

Situation detecting algorithms can be of any degree of complexity, from demons that monitor single

cues (e.g., "snake present") to algorithms that carry out more complex cognitive assessments of

situations and conditions (LeDoux, 1995; Lazarus & Lazarus, 1994; Tooby & Cosmides, 1990a).

Inherent in this approach is the expectation that the human mind has a series of evolved subsystems

designed to represent events in terms of evolutionarily recurrent situations and situational

subcomponents. The operation of these representational systems are not necessarily consciously

accessible. By their structure, they impose an evolutionary organization on representational spaces

that are updated by data inputs. When the representational space assumes certain configurations, aninterpretation is triggered that activates the associated emotion program - corresponding

approximately to what others have called a cognitive appraisal (see, e.g., Lazarus & Lazarus, 1994).

It is important to recognize that the evolutionary past frames the experienced present, because these

situation-detecting algorithms provide the dimensions and core elements out of which many cross-

culturally recurring representations of the world are built. To some extent, the world we inhabit is

shaped by the continuous interpretive background commentary provided by these mechanisms.

5)Algorithms that assign priorities: A given world-state may correspond to more than one situation

at a time, for example, you may be nutritionally depleted and in the presence of a predator. The

prioritizing algorithms define which emotion modes are compatible (e.g., hunger and boredom), and

which are mutually exclusive (e.g., feeding and predator escape). Depending on the relativeimportance of the situations and the reliability of the cues, the prioritizing algorithms decide which

emotion modes to activate and deactivate, and to what degree. Selection, through ancestral mutant


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experiments, would have sorted emotions based on the average importance of the consequences

stemming from each, and the extent to which joint activation was mutually incompatible (or

facilitating). (Prioritizing algorithms can be thought of as a supervisory system operating over all of

the emotions.)

6)An internal communication system: Given that a situation has been detected, the internal

communication system sends a situation-specific signal to all relevant programs and mechanisms;the signal switches them into the appropriate adaptive emotion mode. In addition, information is fed

back into the emotion program from other programs and systems that assess body states, which may

govern the intensity, trajectory, supplantation, or termination of the emotion.

Some modes of activation of the cognitive system are accompanied by a characteristic feeling state,

a certain quality of experience. The fact that we are capable of becoming aware of certain

physiological states - our hearts thumping, bowels evacuating, stomach tightening - is surely

responsible for some of the qualia evoked by emotion states that entrain such responses. The fact

that we are capable of becoming aware of certain mental states - such as retrieved memories of past

events - is probably responsible for other qualia. But it is also possible that in some cases, the

characteristic feeling state that accompanies an emotion mode results (in part) from mechanismsthat allow us to sense thesignalthat activates and deactivates the relevant programs. Such internal

sensory mechanisms - a kind of cognitive proprioception - can be selected for if there are

mechanisms that require as input the information that a particular emotion mode has been activated.

(This might be true, for example, of mechanisms designed to inhibit certain stimulus driven actions

when the conditions are not auspicious.)

7)Each program and physiological mechanism entrained by an emotion program must have

associated algorithms that regulate how it responds to each emotion signal: These algorithms

determine whether the mechanism should switch on or switch off, and if on, what emotion-

specialized performance it will implement. For example, there should be algorithms in the auditory

system that, upon detecting the fear signal (see (6)), reset signal detection thresholds, increasing

acuity for predator-relevant sounds.

What kinds of programs can emotions mobilize?

Any controllable biological process that, by shifting its performance in a specifiable way, would

lead to enhanced average fitness outcomes should have come to be partially governed by emotional

state (see (7) above). Such processes include:

Goals: The cognitive mechanisms that define goal-states and choose among goals in a planning

process should be influenced by emotions. For example, vindictiveness-a specialized subcategory ofanger-may define "injuring the offending party" as a goal state to be achieved. (Although the

evolved functional logic of this process is deterrence, this function need not be represented, either

consciously or unconsciously, by the mechanisms that generate the vindictive behavior.)

Motivational priori ties: Mechanisms involved in hierarchically ranking goals or calibrating other

kinds of motivational and reward systems should be emotion-dependent. What may be extremely

unpleasant in one state, such as harming another, may seem satisfying in another state (e.g.,

aggressive competition may facilitate counter-empathy). Different evolutionarily recurrent

situations predict the presence - visible or invisible - of different opportunities, risks, and payoffs,

so motivational thresholds and valences should be entrained. For example, a loss of face should

increase the motivation to take advantage of opportunities for status-advancement, and decreaseattention to attendant costs.


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I nformation-gatheri ng motivations: Because establishing which situation you are in has enormous

consequences for the appropriateness of behavior, the process of detection should in fact involve

specialized inference procedures and specialized motivations to discover whether certain suspected

facts are true or false. What one is curious about, what one finds interesting, what one is obsessed

with discovering should all be emotion-specific.

Imposed conceptual frameworks: Emotions should prompt construals of the world in terms ofconcepts that are appropriate to the decisions that must be made. When angry, domain-specific

concepts such as social agency, fault, responsibility and punishment will be assigned to elements in

the situation. When hungry, the food-nonfood distinction will seem salient. When endangered,

safety-categorization frames will appear. The world will be carved up into categories based partly

on what emotional state an individual is in.

Perceptual mechanisms: Perceptual systems may enter emotion-specific modes of operation. When

fearful, acuity of hearing may increase. Specialized perceptual inference systems may be mobilized

as well: If you've heard rustling in the bushes at night, human and predator figure-detection may be

particularly boosted, and not simply visual acuity in general. In fact, non-threat interpretations may

be depressed, and the same set of shadows will "look threatening"-that is, given a specificthreatening interpretation such as "a man with a knife"-or not, depending on emotion-state.

Memory: The ability to call up particularly appropriate kinds of information out of long term

memory ought to be influenced. A woman who has just found strong evidence that her husband has

been unfaithful may find herself flooded by a torrent of memories about small details that seemed

meaningless at the time but that now fit into an interpretation of covert activity. We also expect that

what is stored about present experience will also be differentially regulated. Important or shocking

events, for example, may be stored in great detail (as has been claimed about "flashbulb memories",

for example), but other more moderate emotion-specific effects may occur as well.

Attention: The entire structure of attention, from perceptual systems to the contents of high level

reasoning processes, should be regulated by emotional state. If you are worried that your spouse is

late and might have been injured, it is hard to concentrate on other ongoing tasks (Derryberry &

Tucker, 1994), but easy to concentrate on danger-scenarios. Positive emotions may broaden

attentional focus (Fredrickson, 1998).

Physiology: Each organ system, tissue, or process is a potential candidate for emotion-specific

regulation, and "arousal" is insufficiently specific to capture the detailed coordination involved.

Each emotion program should send out a different pattern of instructions (to the face and limb

muscles, the autonomic system, etc.) to the extent that the problems embedded in the associated

situations differ. This leads to an expectation of that different constellations of effects will bediagnostic of different emotion states (Ekman, Levenson & Friesen 1983). Changes in circulatory,

respiratory, and gastrointestinal functioning are well-known and documented, as are changes in

endocrinological function. We expect thresholds regulating the contraction of various muscle

groups to change with certain emotion states, reflecting the probability that they will need to be

employed. Similarly, immune allocation and targeting may vary with disgust, with the potential for

injury, or with the demands of extreme physical exertion.

Communication and emotional expressions: Emotion programs are expected to mobilize many

emotion-specific effects on the subcomponents of the human psychological architecture relevant to

communication. Most notably, many emotion programs produce characteristic species-typical

displays that broadcast to others the emotion state of the individual (Ekman, 1982). Ekman and hiscolleagues have established in a careful series of landmark studies that many emotional expressions

are human universals, both generated and recognized reliably by humans everywhere they have


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been tested (Ekman, 1994). Indeed, many emotional expressions appear to be designed to be

informative, and these have been so reliably informative that humans co-evolved automated

interpreters of facial displays of emotion that decode these public displays into knowledge of others'

mental states. It is surely true that people sometimes "lie" with their faces. But programs for

inferring emotion states from facial displays would not have evolved unless doing so created a net

advantage for the inferer, suggesting that these inferences were warranted more often than not.

Two things are communicated by an authentic emotional expression: (1) that the associated emotion

program has been activated in an individual, providing observers with information about the state of

that individual's mental programs and physiology (e.g., I am afraid); and (2) the identity of the

evolutionarily recurrent situation being faced, in the estimation of the signaler (e.g., the local world

holds a danger). Both are highly informative, and emotional expressions provide a continuous

commentary on the underlying meaning of things to companions. This provokes the question: Why

did selection build facial, vocal and postural expressions at all? More puzzlingly, why are they often

experienced as automatic and involuntary?

From an evolutionary perspective, sometimes it is beneficial to provide information to others, and

other times it is injurious, so most evolved communication systems involve close regulation ofwhether to transmit information or not. Usually this leads to a system, like language, in which the

decision to communicate something (or not) can be made by the individual in detailed response to

the immediate circumstances. The apparent selective disadvantages of honestly and automatically

broadcasting one's emotional state have led Fridlund (1994), for example, to argue that expressions

must be voluntary and intentional communications largely unconnected to emotion state.

Undoubtedly they sometimes are. But even when people deliberately lie, microexpressions of face

and voice often leak out (Ekman, 1985), suggesting that certain emotion programs do in fact create

involuntarily emitted signals that reliably broadcast the person's emotion state. Why?

Natural selection has shaped emotion programs to signal their activation, or not, on an emotion by

emotion basis. Summing for each emotion program considered by itself (jealousy, loneliness,

disgust, predatoriness, parental love, sexual attraction, gratitude, fear), there was a net benefit or

cost to having others know that mental state, averaged across individuals over evolutionary time.

For those recurrent situations in which, on average, it was beneficial to share one's emotion state

(and hence assessment of the situation) with those one was with, species-typical facial and other

expressions of emotion were constructed by selection. For example, fear was plausibly beneficial to

signal, because it signaled the presence of a danger that might also menace one's kin and

cooperators, and also informed others in a way that might recruit assistance.

Nevertheless, averaged over evolutionary time, it was functional for the organism to signal the

activation of onlysomeemotion states. The conditions favoring signaling an emotion are hard tomeet, so only some emotions out of the total species-typical set are associated with distinctive,

species-typical facial expressions. There should be a larger set of emotions that have no automatic

display. Jealousy, guilt, or boredom are all genuine emotions lacking distinctive signals. This

changes the question from: Why are emotions automatically signaled? to Why aresomeemotions

automatically signaled? When selection is neutral, the signs of an emotion should only be the

byproducts of whatever is necessary to run the emotion program, without any selection to make the

cues informative. When selection disfavors others knowing the organism's internal state, selection

should suppress and obscure external cues identifying internal states. Precisely because they

publicly signal themselves, our attention goes disproportionately to the subset of emotions that do

come equipped with emotional expressions. We think it likely that this had an impact on the history

of emotion research.


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Three factors govern whether transmitting information will be beneficial or harmful: the signaler's

relationship to the audience, the nature of the information that an emotion signal would release, and

the computational overhead of computing the benefits and costs of information sharing on a case by

case basis in order to regulate whether to make a broadcast (Tooby & Cosmides, 1996). In general

(but with some notable exceptions), the closer the cooperative relationship and shared fitness

interests, the more beneficial it is to share information; the more distant and adversarial the

relationship, the more harmful it is. For this reason, we expect that circuits have evolved thatregulate global emotional expressiveness depending on whether one is (apparently) alone, with

people one shares interests with, or with social antagonists such as enemies or higher ranking

individuals where leakage of damaging information should be suppressed. This global regulation

may be largely automatic and nonconscious, and may involve open parameters set culturally and

developmentally. Other things being equal, individuals will be shyer and less spontaneous with

strangers (creating problems in public speaking), and more expressive with intimates. Similarly, it

may be that male-female differences in emotional expressiveness arise from an evolutionary history

in which males were on average more often in the presence of potential adversaries. Of course, it is

beneficial to the transmitter to share certain types of information with adversaries, such as anger,

triumph, or surrender, but many other types (fear of adversaries, pain, anxiety about weaknesses)

ought to be suppressed.

The nature of the information broadcast has two components: (1) reliable consequences, predicted

by the identity of the emotion, and (2) context-specific consequences (Tooby & Cosmides, 1996).

The first component can be handled by automating the broadcast of the identity of those emotions

that, on average, reliably produced a benefit when shared: Approval or disapproval assist in

communicating to social interactants one's values; fear communicated the nature of a common

danger; disgust communicated avoidance and spoilage; anger, a conflict of values with a

willingness to enforce one's values with a sanction. The second, context-specific component

requires computational circuitry to calculate the consequences of releasing a piece of information

into the social world - a very complex set of computations. The benefit gained by inhibiting release

of an expression on a case by case basis must be large enough to offset the cost of suchcomputations for selection to favor the evolution of such regulatory circuits. The overall result of

these selection pressures would be that some emotions would evolve to be automatically broadcast,

others would not evolve a signal, and a third category would evolve circuits that regulate the

broadcast to some extent, just as it is in language.

Nevertheless, the automatic, involuntary expression of many emotions is a key feature of the

biology and social life of our species, and their presence provides powerful evidence that ancestral

humans spent a large portion of their time with close cooperators, as opposed to antagonists and

competitors. Indeed, species ought to vary in the magnitude of automatic emotion signaling, and in

which emotions are signaled, based on the social ecology of the species. Highly cooperative socialspecies, such as canids, are expected to (and appear to) have a rich repertoire of emotion signals,

while more solitary species, such as felids, should have fewer emotion signals.

Behavior:All psychological mechanisms are involved in the generation and regulation of behavior,

so obviously behavior will be regulated by emotion state. More specifically, however, mechanisms

proximately involved in the generation of actions (as opposed to processes like face recognition that

are only distally regulatory) should be very sensitive to emotion state. Not only may highly

stereotyped behaviors of certain kinds be released (as during sexual arousal or rage, or as with

species-typical facial expressions and body language), but more complex action-generation

mechanisms should be regulated as well. Specific acts and courses of action will be more available

as responses in some states than in others, and more likely to be implemented. Emotion modeshould govern the construction of organized behavioral sequences that solve adaptive problems.


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Biologists, psychologists, and economists who adopt an evolutionary perspective have recognized

that many forms of social interactions can be modeled using game theory (Maynard Smith 1982). If

the EEA imposes certain evolutionarily repeated games, then the "strategies" (the evolved cognitive

programs that govern behavior in those contexts) should evolve in the direction of choices that lead

to the best expected fitness payoffs. The strategy activated in the individual should match the game

(e.g., exchange) and the state of play in the game (e.g., just been cheated), a process that requires

the system of cues, situation-detection, and so on, already discussed. So, different emotion andinference programs or subprograms may have evolved to correspond to various evolved games,

including zero sum competitive games, positive sum exchange games, coalitional lottery games,

games of aggressive competition corresponding to "chicken", and so on (for exchange, see

Cosmides, 1989; Cosmides & Tooby, 1992). Corresponding emotion programs guide the individual

into the appropriate interactive strategy for the social "game" being played, given the state of play.

Surprisingly, for some games, rigid obligatory adherence to a prior strategy throughout the game is

better than the ability to revise and change strategies ("voluntarily") in the light of events. If an

individual contemplating a course of action detrimental to you knew you would take revenge,

regardless of the magnitude of the punishment to you that they might unleash, then they are less

likely to take such harmful action. This may translate into emotion programs in which the desire to

attempt certain actions should be overwhelming, to the point where the actions are experienced ascompulsory. In the grip of such programs, competing programs, including the normal integration of

prudential concerns and social consequences, are muted or terminated. For example, the desire to

avenge a murder or an infidelity is often experienced in this way, and are even culturally recognized

as "crimes of passion" (Daly & Wilson, 1988). In modern state societies, where there are police

who are paid to punish and otherwise enforce agreements, it is easy to underestimate the importance

that deterrence based on the actions of oneself and one's coalition had in the Pleistocene. Hirshleifer

(1987) and Frank (1988) are evolutionary economists who have pursued this logic the furthest,

arguing that many social behaviors are the result of such "commitment problems".

Special ized inference: Research in evolutionary psychology has shown "thinking" and reasoning is

not a unitary category, but is carried out by a variety of specialized mechanisms. So, instead ofemotion activating or depressing "thinking" in general, the specific emotion program activated

shouldselectivelyactivate appropriate specialized inferential systems, such as cheater detection

(Cosmides 1989; Cosmides & Tooby 1989, 1992), bluff detection (Tooby & Cosmides, 1989),

precaution detection (Fiddick, Cosmides & Tooby, in press), attributions of blame and

responsibility, and so on. We are presently conducting research to see whether, as predicted, fear

influences precautionary reasoning, competitive loss regulates bluff detection, and so on.

Reflexes: Muscular coordination, tendency to blink, threshold for vomiting, shaking, and many

other reflexes are expected to be regulated by emotion programs to reflect the demands of the

evolved situation.

Learning: Emotion mode is expected to regulate learning mechanisms. What someone learns from

stimuli will be greatly altered by emotion mode, because of attentional allocation, motivation,

situation-specific inferential algorithms, and a host of other factors. Emotion mode will cause the

present context to be divided up into situation-specific functionally appropriate categories so that

the same stimuli and the same environment may be interpreted in radically different ways,

depending on emotion state. For example, which stimuli are considered similar should be different

in different emotion states, distorting the shape of the individual's psychological "similarity space"

(Shepard 1987). Highly specialized learning mechanisms might be activated, such as those that

control food aversions (Garcia, 1990) or predator learning (Mineka & Cooke, 1985), or fear

conditioning (LeDoux, 1995). Happiness is expected to signal the energetic opportunity for play,and allow other exploratory agendas to be expressed (Frederickson, 1998).


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Af fective coloration of events and stimul i as a form of learning: A behavioral sequence is

composed of many acts. Each of these acts can be thought of as an intermediate "factor" in the

production of a behavioral sequence (to use economic terminology). Determining which courses of

action are worthwhile and which are not is a major informational problem. The payoff of each

"factor of production"-of each act in the sequence-must be computed before an agent could

determine whether the whole sequence was worthwhile. Every time there is a change in the world

(e.g., death of a spouse, the acquisition of a better foraging tool) that affects the probable payoff ofan act, or new information that allows a better evaluation of payoffs, this value needs to

recomputed. Evaluating entire chains as units is not sufficient, because each item in a chain (staying

behind from the hunt, making a tool, borrowing materials from a friend, etc.) may be used in

another unique sequence at a later time. Therefore, effort, fitness token-payoffs (rewards),

opportunity costs, risks, and many other components of evaluation need to be assigned continually

to classes of acts. For this reason, there should be mechanisms that assign hedonic and other

motivationally informative values to acts (e.g., "dangerous", "painful", "effort-consuming",

"informative", "fun", "socially approved"), tallied as intermediate weights in decision processes.

Our stream of actions and daily experiences will be affectively "colored" by the assignment of these

hedonic values. If our psychological mechanisms were not using present outcomes to assign a

common internal currency of hedonic weights to classes of acts, there would be no function tosuffering, joy, and so on. Emotion mode obviously impacts the assignment of hedonic values to

acts.

Energy level, effort allocation, and mood: Overall metabolic budget will be regulated by emotion

programs, as will specific allocations to various processes and facilitation or inhibition of specific

activities. The effort that it takes to perform given tasks will shift accordingly, with things being

easier or more effortful depending on how appropriate they are to the situation reflected by the

emotion (Tooby & Cosmides, 1990a). Thus, fear will make it more difficult to attack an antagonist,

whereas anger will make it easier. The confidence with which a situation has been identified (i.e.,

emotional clarity) should itself regulate the effortfulness of situation-appropriate activities.

Confusion (itself an emotional state) should inhibit the expenditure of energy on costly behavioralresponses and should motivate more information gathering and information analysis. Nesse (1990)

has suggested that the function of mood is to reflect the propitiousness of the present environment

for action, a hypothesis with many merits. We hypothesized (Tooby & Cosmides, 1990a) a similar

function of mood, based on recognizing that the action-reward ratio of the environment is not a

function of the environment alone, but an interaction between the structure the environment and the

individual's present understanding of it. (By "understanding", we mean the correspondence between

the structure of the environment, the structure of the algorithms, and the weightings and other

information they use as parameters). The phenomenon that should regulate this aspect of mood is a

perceived discrepancy between expected and actual payoff. The suspension of behavioral activity

accompanied by very intense cognitive activity in depressed people looks like an effort toreconstruct models of the world so that future action can lead to payoffs, in part through stripping

away previous valuations that led to unwelcome outcomes. Depression should be precipitated by (1)

a heavy investment in a behavioral enterprise that was expected to lead to large payoffs that either

failed to materialize or were not large enough to justify the investment; or (2) insufficient

investment in maintaining a highly valued person or condition that was subsequently lost (possibly

as a consequence); or (3) gradual recognition by situation-detectors that one's long-term pattern of

effort and time expenditure has not led to a sufficient level of evolutionarily meaningful reward,

when implicitly compared to alternative life paths (the condition of Dickens' Scrooge).

Discrepancies between expected and actual payoff can occur in the other direction as well: Joy or

precipitated surges of happiness are an emotion program that evolved to respond to the condition of

an unexpectedly good outcome. They function to recalibrate previous value states which had led tounderinvestment in or underexpectation for the successful activities or choices. Moreover, energy

reserves that were being sequestered under one assumption about future prospects can be released


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given new, more accurate expectations about a more plentiful or advantageous future. Similarly,

one can be informed of bad outcomes to choices not made: For example, one might find out that a

company one almost invested in went

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Evolutionary Psychology and the Emotions.docx